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Artificial neural network analysis of Moroccan solar potential

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  • Ouammi, Ahmed
  • Zejli, Driss
  • Dagdougui, Hanane
  • Benchrifa, Rachid

Abstract

An artificial neural network (ANN) model is used to forecast the annual and monthly solar irradiation in Morocco. Solar irradiation data are taken from the new Satellite Application Facility on Climate Monitoring (CM-SAF)-PVGIS database. The database represents a total of 12 years of data from 1998 to 2010. In this paper, the data are inferred using an ANN algorithm to establish a forward/reverse correspondence between the longitude, latitude, elevation and solar irradiation. Specifically, for the ANN model, a three-layered, back-propagation standard ANN classifier is considered consisting of three layers: input, hidden and output layer. The learning set consists of the normalised longitude, latitude, elevation and the normalised mean annual and monthly solar irradiation of 41 Moroccan sites. The testing set consists of patterns just represented by the input component, while the output component is left unknown and its value results from the ANN algorithm for that specific input. The results are given in the form of the annual and monthly maps. They indicate that the method could be used by researchers or engineers to provide helpful information for decision makers in terms of sites selection, design and planning of new solar plants.

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  • Ouammi, Ahmed & Zejli, Driss & Dagdougui, Hanane & Benchrifa, Rachid, 2012. "Artificial neural network analysis of Moroccan solar potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4876-4889.
    • Handle: RePEc:eee:rensus:v:16:y:2012:i:7:p:4876-4889
    DOI: 10.1016/j.rser.2012.03.071
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    18. Kousksou, T. & Allouhi, A. & Belattar, M. & Jamil, A. & El Rhafiki, T. & Zeraouli, Y., 2015. "Morocco's strategy for energy security and low-carbon growth," Energy, Elsevier, vol. 84(C), pages 98-105.
    19. Yadav, Amit Kumar & Chandel, S.S., 2015. "Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model," Renewable Energy, Elsevier, vol. 75(C), pages 675-693.
    20. Žalik, Mitja & Mongus, Domen & Lukač, Niko, 2024. "High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learning," Renewable Energy, Elsevier, vol. 222(C).
    21. Alami Merrouni, Ahmed & Elwali Elalaoui, Fakhreddine & Mezrhab, Ahmed & Mezrhab, Abdelhamid & Ghennioui, Abdellatif, 2018. "Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco," Renewable Energy, Elsevier, vol. 119(C), pages 863-873.
    22. Yadav, Amit Kumar & Malik, Hasmat & Chandel, S.S., 2014. "Selection of most relevant input parameters using WEKA for artificial neural network based solar radiation prediction models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 509-519.
    23. Kousksou, T. & Allouhi, A. & Belattar, M. & Jamil, A. & El Rhafiki, T. & Arid, A. & Zeraouli, Y., 2015. "Renewable energy potential and national policy directions for sustainable development in Morocco," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 46-57.

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